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DNA Commission of the International Society of Forensic Genetics: Recommendations on the Evaluation of STR Typing Results That May Include Drop-Out and/or Drop-In Using Probabilistic Methods

NCJ Number
Forensic Science International: Genetics Volume: 6 Issue: 6 Dated: December 2012 Pages: 679-688
P. Gill; L. Gusmao; H. Haned; W.R. Mayr; N. Morling; W. Parson; L. Prieto; M. Prinz; H. Schneider; B.S. Weir; P.M. Schneider
Date Published
December 2012
10 pages

The authors of this study give recommendations on how to estimate probabilities considering drop-out, Pr(D), and drop-in, Pr(C).


DNA profiling of biological material from scenes of crimes is often complicated because the amount of DNA is limited and the quality of the DNA may be compromised. Furthermore, the sensitivity of STR typing kits has been continuously improved to detect low level DNA traces. This may lead to (1) partial DNA profiles and (2) detection of additional alleles. There are two key phenomena to consider: allelic or locus 'drop-out', i.e. 'missing' alleles at one or more genetic loci, while 'drop-in' may explain alleles in the DNA profile that are additional to the assumed main contributor(s). The drop-in phenomenon is restricted to 1 or 2 alleles per profile. If multiple alleles are observed at more than two loci then these are considered as alleles from an extra contributor and analysis can proceed as a mixture of two or more contributors. Here, the authors give recommendations on how to estimate probabilities considering drop-out, Pr(D), and drop-in, Pr(C). For reasons of clarity, we have deliberately restricted the current recommendations considering drop-out and/or drop-in at only one locus. Furthermore, they offer recommendations on how to use Pr(D) and Pr(C) with the likelihood ratio principles that are generally recommended by the International Society of Forensic Genetics (ISFG) as measure of the weight of the evidence in forensic genetics. Examples of calculations are included. An Excel spreadsheet is provided so that scientists and laboratories may explore the models and input their own data. (Published Abstract)